<?xml version="1.0" encoding="utf-8"?>
<rss version="2.0">
  <channel>
    <title>Data Engineer/Databricks - Careerwise RSS Feed</title>
    <link>https://jobs.co.uk/job/data-engineerdatabricks-careerwise--802d4003-f065-4351-a08a-4e66e394fc83</link>
    <description>RSS feed for Data Engineer/Databricks at Careerwise.</description>
    <language>en-gb</language>
    <lastBuildDate>Wed, 08 Jul 2026 14:55:34 GMT</lastBuildDate>
    <item>
      <title>Data Engineer/Databricks - Careerwise</title>
      <link>https://jobs.co.uk/job/data-engineerdatabricks-careerwise--802d4003-f065-4351-a08a-4e66e394fc83</link>
      <guid>https://jobs.co.uk/job/data-engineerdatabricks-careerwise--802d4003-f065-4351-a08a-4e66e394fc83</guid>
      <pubDate>Wed, 08 Jul 2026 11:52:31 GMT</pubDate>
      <description>Location: London | Salary: 80000.00-80000.00 Annual | Type: Permanent | Data Engineer (Databricks) is required by a global software company to join its AI and Data team and play a key role in designing, developing, and maintaining data solutions. Responsibilities:  Designing, developing, orchestrating, maintaining, and optimizing robust data pipelines and data solutions using Databricks and the Azure ecosystem. Building and enhancing structured data models that transform raw data into reliable, business-ready information. Implementing data loading, transformation, exploration, and processing solutions. Troubleshooting, analysing, and optimizing ETL processes while performing root cause analysis to improve reliability and performance. Supporting CI/CD processes and Agile delivery practices using Azure DevOps, Repos, and pipeline automation. Creating and maintaining technical documentation covering workflows, data models, pipelines, and processes.  Required experience and skills:  Extensive experience in a Data Engineering role delivering data pipelines, data warehouses, data lakes, and lakehouse solutions for BI, reporting, and analytics.  Star Schema, fact and dimension modelling, SCD, and CDC.  Strong hands-on experience Databricks including Workflows...</description>
      <category>Permanent</category>
    </item>
  </channel>
</rss>